Claudio Semini (MSc 2005, PhD 2010) is the head of the Dynamic Legged Systems (DLS) lab at Istituto Italiano di Tecnologia (IIT) that developed a number of high-performance hydraulic robots, including HyQ, HyQ2Max, and HyQReal. He holds an MSc degree from ETH Zurich in electrical engineering and information technology. He spent 2 years in Tokyo for his research: MSc thesis at the Hirose Lab at Tokyo Tech and staff engineer at the Toshiba R&D center in Kawasaki working on mobile service robotics. During his PhD and subsequent PostDoc at IIT, he developed the quadruped robot HyQ and worked on its control. Since 2012 he leads the DLS lab. Claudio Semini is the author and co-author of more than 100 peer-reviewed publications in international journals and conferences and he received several awards for them. He is also a co-founder of the Technical Committee on Mechanisms and Design of the IEEE-RAS Society. He is/was the coordinator/partner of several EU-, National and Industrial projects (including HyQ-REAL, INAIL Teleop, Moog@IIT joint lab, ESA-ANT, etc). His research interests include the construction and control of highly dynamic and versatile legged robots for field application in real-world operations, locomotion, hydraulic drives, and others.
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Head of the Dynamic Legged Systems (DLS) research lineSenior Researcher Tenured - Principal Investigator
Dynamic Legged Systems
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Abdalla A., Focchi M., Orsolino R., Semini C.
An Effecient Paradigm For Feasibility Guarantees in Legged Robots
Transactions on Robotics
Bertol D. W., Fink G., Nisticò Y., Cerilli G., Marchitto M., Semini C.
A Practical Real-Time Distributed Software Framework for Mobile Robots
2023 IEEE International Conference on Robotics and Automation (ICRA)
Bratta A., Focchi M., Rathod N., Semini C.
Optimization-Based Reference Generator for Nonlinear Model Predictive Control of Legged Robots
Robotics, vol. 12, (no. 1)
Roscia F., Cumerlotti A., Del Prete A., Semini C., Focchi M.
Orientation Control System: Enhancing Aerial Maneuvers for Quadruped Robots
Sensors, vol. 23, (no. 3)
Guadagna P., Fernandes M., Chen F., Santamaria A., Teng T., Frioni T., Caldwell D.G., Poni S., Semini C., Gatti M.
Using deep learning for pruning region detection and plant organ segmentation in dormant spur-pruned grapevines
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